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Track structures belong to nanomaterials. Therefore, when studying such structures, it is important to take into account the general properties of nanomaterials. It is important to predict the structural features of the ...

Mathematical models, usually implemented in computer programs known as computer models, are widely used in all areas of science and technology to represent complex systems in the real world. However, computer models are ...

Abstract Computer models and simulations have provided enormous benefits to researchers in the natural and social sciences, as well as many areas of philosophy. However, to date, there has been little attempt to use comp...

Kriging models are used in many scientific disciplines to investigate the behavior of physical systems. In the Kriging model (KM), the response of the computer simulation code (CSC) is considered to have a Gaussian proce...

The paper presents the results of computer modeling of the proposed functional-electrical circuit of integrated signal converters (ISC) from photosensitive elements based on CMOS operational amplifiers, which is intended...

Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography (CGH). Current data-driven deep learning algorithms face the challenge that the labeled training datasets...

The popularity of deep learning has boosted computer-generated holography (CGH) as a vibrant research field, particularly physics-driven unsupervised learning. Nevertheless, present unsupervised CGH models have not yet e...

Abstract Effort estimation remains a persistent challenge in agile software development, particularly at the user story level where iterative delivery is emphasized. Inaccurate estimations can result in misallocated reso...

Forestry knowledge is highly specialized and broad in scopeand is particularly sensitive to regulations and practical standards. To address the knowledge gaps, terminological ambiguities, and factual inaccuracies that ge...

Under the guidance of the "dual carbon" goals, green electricity has become the core carrier of the new energy transition. However, issues such as mismatched supply and demand of  green electricity, information asymmetr...

Car classification is important in daily life because there are many distinct types of automobiles made by various manufacturers. Although there are numerous methods for classifying autos, machine learning technologies h...

This study presents Duygu-Turk, a novel deep learning-based sentiment analysis framework specifically designed for the Turkish language which is characterized by its agglutinative and morphologically rich structure. Unli...

Dynamic gesture recognition is a core technology for human–computer interaction, yet existing methods face prominent limitations in hand spatial topology modeling, long–short-term temporal feature fusion, and general...

Abstract Brain-computer interfaces (BCIs) were initially created to help individuals with disabilities control devices and communicate without muscle movement. Today, BCIs are used for prosthetic control, cognitive enhan...

Object detection is a central task in computer vision, with wide adoption in real-world applications such as surveillance systems, autonomous driving, healthcare monitoring, and smart devices. Models such as YOLOv8, SSD,...

Abstract In terms of global health, cardiovascular diseases remain an emerging challenge, for which early estimation for timely medical treatment proves crucial. In this paper, an estimate of this challenge has been pres...

Background Identifying priority projects in industry–education integration is critical for optimizing policy support and resource allocation. While prior studies have primarily relied on qualitative assessments, there ...

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffi...

INTRODUCTION: With the deepening of China's "Dual Carbon" goals, the scale of photovoltaic (PV) installations continues to expand, placing stringent requirements on the accuracy, scenario adaptability, and robustness of ...

BackgroundThe integration of artificial intelligence (AI) into emergency medicine holds promise for enhancing early diagnosis and clinical decision-making. Traditional diagnostic approaches often rely on physician judgme...

Abstract The current English grammar error correction model still has low accuracy when dealing with complex sentences and long sentence dependencies. Therefore, this study proposes a Sequence-to-Sequence (Seq2Seq) model...

Objective: This paper tackles the cross-sessions variability of electroencephalography-based brain-computer interfaces (BCIs) in order to avoid the lengthy recalibration step of the decoding method before every use. Meth...

In recent years, the frequency and complexity of financial fraud have been rising and have become an urgent challenge for the global financial system. Traditional rule-based detection methods struggle to cope with new ty...

E-commerce companies face fierce competition. For e-commerce companies to succeed, they must keep and attract customers by offering them the best affordable services. Taking appropriate and timely actions to keep custome...